Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...
Diffusion tensor imaging (DTI), based on the diffusion-weighted imaging (DWI) data acquired from magnetic resonance experiments, has been widely used to analyze the physical structure of white-matter ...
A new technical paper titled “A Tensor Compiler for Processing-In-Memory Architectures” was published by researchers at ...
Dr. James McCaffrey of Microsoft Research presents the fundamental concepts of tensors necessary to establish a solid foundation for learning how to create PyTorch neural networks, based on his ...
Hosted on MSN
What are tensors?
Tensors play a pivotal role in AI and deep learning systems, and share a common heritage with both physics and advanced mathematics. All of which makes it extremely difficult to lock down a definitive ...
New computational techniques, 'HighLight' and 'Tailors and Swiftiles,' could dramatically boost the speed and performance of high-performance computing applications like graph analytics or generative ...
Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback